Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Identification of Rx2 binding loci in medaka by iDamID-seq

ABSTRACT: We have improved the DamID method to make it applicable for vertebrate life specimens. We use iDamID-seq to profile the binding profile of the transcription factor Rx2 in medaka embryos at stage 22 of development. We compare two replicates of the fusion Dam-Rx2 against two replicates of the fusion Dam-GFP as control. Medaka embryos at 1-cell stage were injected with mRNA transcribed in vitro from one of the two Dam fusions. The embryos were allowed to grow in normal conditions up to stage 22. The genomic DNA was isolated and treated to extract only the DpnI fragments that had adenine methylation. These fragments were subjected to deep sequencing.

INSTRUMENT(S): Illumina HiSeq 2000

ORGANISM(S): Oryzias latipes

SUBMITTER: Arturo Gutierrez-Triana

PROVIDER: E-MTAB-4610 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

iDamIDseq and iDEAR: an improved method and computational pipeline to profile chromatin-binding proteins.

Gutierrez-Triana Jose Arturo JA Mateo Juan L JL Ibberson David D Ryu Soojin S Wittbrodt Joachim J

Development (Cambridge, England) 20161005 22

DNA adenine methyltransferase identification (DamID) has emerged as an alternative method to profile protein-DNA interactions; however, critical issues limit its widespread applicability. Here, we present iDamIDseq, a protocol that improves specificity and sensitivity by inverting the steps DpnI-DpnII and adding steps that involve a phosphatase and exonuclease. To determine genome-wide protein-DNA interactions efficiently, we present the analysis tool iDEAR (iDamIDseq Enrichment Analysis with R) ...[more]

PMID: 27707796

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Project description:The anabolic androgen 17M-NM-2-trenbolone (TB) can cause masculinization and reduce fecundity of fish. However, the underlying mechanisms of various biological pathways including metabolism, biosynthesis etc. are largely unknown. Here, we evaluated the effects of TB using the medaka DNA microarray representing 36,398 genes. Larval medaka, Oryzias latipes, (within 24 hrs posthatch) were exposed to TB at various concentrations (2, 6, 20, 60, 100, 200 ng/L) for up to 7 days. Dose-response relationships in gene expression levels of the categorized genes were analyzed using the cumulative chisquared method. Microarray analyses of the TB-exposed larvae showed that 117 and 32 genes were determined as up and down-regulated genes, respectively. The most significant GO term for biological process identified within this gene list was lipid metabolic process, which contained 26 genes in up-regulated genes. In this category, M-bM-^@M-^\cholesterol biosynthetic processM-bM-^@M-^] was highlighted as an important subcategory with 15 genes, including hydroxymethylglutaryl-CoA synthase cytoplasmic, squalene monooxygenase, lanosterol synthase etc. RT-PCR measurements in these genes were consistent with the microarray results in the direction and magnitude of these changes in gene expression. On the other hands, in the category of M-bM-^@M-^\sexual differentiation and developmentM-bM-^@M-^], genes related to hypothalamic-pituitary-gonadal (HPG) axis were not affected by TB treatment except for one gene encoded to cytochrome P450 19A1. Genes related to oogenesis, such as choriogenins and vitellogenins were weakly down regulated at 2-200 ng/L of TB. Our findings demonstrate that genes encoding cholesterol synthesis pathway via the mevalonate pathway were controlled by TB in larval medaka. TB concentrations used were 0 (control), 2, 6, 20, 60, 100 and 200 ng/L for 7 days of exposure. Each TB treatment had 90 larval medaka for each chamber. At day 7 of the exposures, triplicate samples (30 larvae/sample) from each chamber respectively were collected, flash-frozen in liquid nitrogen, and stored in liquid nitrogen until RNA extraction.

Dataset Information

Identification of Rx2 binding loci in medaka by iDamID-seq

Publications

iDamIDseq and iDEAR: an improved method and computational pipeline to profile chromatin-binding proteins.

Similar Datasets

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